Aktives Forschungsdatenmanagement

Neuroth, Heike; Engelhardt, Claudia; Klar, J.; Ludwig, Jens; Enke, H.

doi:10.1515/abitech-2018-0008

Cited by 4 publications

(6 citation statements)

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“…However, they are somewhat undecided about the quality of DMP guidelines and templates, indicating that method- and discipline-specific templates for the creation of DMPs are missing. Existing efforts to provide DMP templates, online guides e.g., Open Science Framework Guides , DMP tools (e.g., RDMO 19 ), or DMP guidelines (e.g., Ref. 49 ) should therefore be improved to better address specific user needs.…”

Section: Resultsmentioning

confidence: 99%

“…Other networks and public as well as commercial efforts have contributed data management systems, electronic lab notebooks, or tools to create data management plans. [15][16][17][18][19] Several organizations foster the international collaboration of bioimaging scientists supporting, e.g., access to high-end instrumentation (Euro-BioImaging) and knowledge exchange (Global BioImaging, GBI, and the network on Quality Assessment and Reproducibilty for Instruments and Images in Light Microscopy, QUAREP-LiMi 20,21 ). In Germany, the non-profit association German BioImaging -Society for Microscopy and Image Analysis e.V.…”

Section: Introductionmentioning

confidence: 99%

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Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

Schmidt

Hanne²,

Moore³

et al. 2022

F1000Res

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Background: Knowing the needs of the bioimaging community with respect to research data management (RDM) is essential for identifying measures that enable adoption of the FAIR (findable, accessible, interoperable, reusable) principles for microscopy and bioimage analysis data across disciplines. As an initiative within Germany's National Research Data Infrastructure, we conducted this community survey in summer 2021 to assess the state of the art of bioimaging RDM and the community needs. Methods: An online survey was conducted with a mixed question-type design. We created a questionnaire tailored to relevant topics of the bioimaging community, including specific questions on bioimaging methods and bioimage analysis, as well as more general questions on RDM principles and tools. 203 survey entries were included in the analysis covering the perspectives from various life and biomedical science disciplines and from participants at different career levels. Results: The results highlight the importance and value of bioimaging RDM and data sharing. However, the practical implementation of FAIR practices is impeded by technical hurdles, lack of knowledge, and insecurity about the legal aspects of data sharing. The survey participants request metadata guidelines and annotation tools and endorse the usage of image data management platforms. At present, OMERO (Open Microscopy Environment Remote Objects) is the best known and most widely used platform. Most respondents rely on image processing and analysis, which they regard as the most time-consuming step of the bioimage data workflow. While knowledge about and implementation of electronic lab notebooks and data management plans is limited, respondents acknowledge their potential value for data handling and publication. Conclusion: The bioimaging community acknowledges and endorses the value of RDM and data sharing. Still, there is a need for information, guidance, and standardization to foster the adoption of FAIR data handling. This survey may help inspiring targeted measures to close this gap.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

Schmidt

Hanne²,

Moore³

et al. 2022

F1000Res

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“…The DMP community acknowledges the importance of maintaining a diverse range of tools [1] to meet the specific needs of different research domains. Several tools have been developed to assist users in the preparation of high-quality DMPs, such as Data Stewardship Wizard [27], DMP online [60], DMP tools [2], DMP Canvas Generator , EzDMP [37], DMPRoadmap [61], RDMO [38,42], Research Data Manager (UQRDM) [31], DataWiz [32], ARGOS [33], UWADMP [36], DMPTY [35] and easyDMP [34]. Table 1 summarizes their key characteristics, programming languages, current templates, customizability, openness, and convenience, in comparison to DataPLAN.…”

Section: Comparison With Existing Dmp Toolsmentioning

confidence: 99%

“…Multiple tools have been developed to tackle the challenges described above [2,[27][28][29][30][31][32][33][34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

DataPLAN: a web-based data management plan generator for the plant sciences

Zhou,

Beier,

Brilhaus

et al. 2023

Preprint

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Research Data Management (RDM) is a system for the effective handling of research data that enables scientists to structure their research questions and ensure best practices throughout the data lifecycle, from acquisition, computation and annotation to data publication and re-use. Data management plans (DMPs) are documents that formally set out the RDM of a project and are required by many funding bodies. DMPs help to organize and structure RDM strategies, thus promoting data findability, accessibility, interoperability and reusability (FAIR). Although DMPs incorporate methods and standards that can be reused by different research projects, the standardization of DMP content is not as evident as the standardization of RDM practices and data/metadata. To address this issue in the plant sciences, we developed DataPLAN — a tool that combines a questionnaire with pre-written standardized responses. We wrapped the questionnaire in a serverless single-page web application that can then generate standardized responses from DMP templates. The current templates cater to plant research grant proposals for Horizon 2020, Horizon Europe and the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG). In the future the range of templates will be extended to accommodate other funding schemes, thereby enabling more users to generate their own templates. The DataPLAN web application is open-source and does not require an internet connection. By utilizing DataPLAN, the workload associated with creating, updating, and adhering to DMPs is significantly reduced.

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“…Compliance with the requirements of different funding bodies is time-consuming, and multiple tools have been developed to tackle the resulting challenges [2,[18][19][20][21][22][23][24][25][26][27][28][29]. These tools help researchers to write comprehensive DMPs by providing a structured framework and guidelines.…”

Section: Figurementioning

confidence: 99%

DataPLAN: A Web-Based Data Management Plan Generator for the Plant Sciences

Zhou,

Beier,

Brilhaus

et al. 2023

Data

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Research data management (RDM) combines a set of practices for the organization, storage and preservation of data from research projects. The RDM strategy of a project is usually formalized as a data management plan (DMP)—a document that sets out procedures to ensure data findability, accessibility, interoperability and reusability (FAIR-ness). Many aspects of RDM are standardized across disciplines so that data and metadata are reusable, but the components of DMPs in the plant sciences are often disconnected. The inability to reuse plant-specific DMP content across projects and funding sources requires additional time and effort to write unique DMPs for different settings. To address this issue, we developed DataPLAN—an open-source tool incorporating prewritten DMP content for the plant sciences that can be used online or offline to prepare multiple DMPs. The current version of DataPLAN supports Horizon 2020 and Horizon Europe projects, as well as projects funded by the German Research Foundation (DFG). Furthermore, DataPLAN offers the option for users to customize their own templates. Additional templates to accommodate other funding schemes will be added in the future. DataPLAN reduces the workload needed to create or update DMPs in the plant sciences by presenting standardized RDM practices optimized for different funding contexts.

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Aktives Forschungsdatenmanagement

Cited by 4 publications

References 0 publications

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey

DataPLAN: a web-based data management plan generator for the plant sciences

DataPLAN: A Web-Based Data Management Plan Generator for the Plant Sciences

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